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Intelligent computational solutions for constitutive modelling of materials in finite element analysis

Intelligent computational solutions for constitutive modelling of materials in finite element analysis

Javadi, Akbar A., Faramarzi, Asaad and Alani, Amir (2012) Intelligent computational solutions for constitutive modelling of materials in finite element analysis. In: ACME2012: Proceedings of the 20th UK National Conference of the Association for Computational Mechanics in Engineering. The University of Manchester, Manchester, UK, pp. 321-324. ISBN 9780903808064

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Abstract

In this paper recent developments in application of Evolutionary Polynomial Regression (EPR) in material modelling and its implementation in finite element analysis (FEA) is presented. EPR is a hybrid data mining technique that searches for symbolic structures (representing the behaviour of a system) using a genetic algorithm and estimates the constant values by the least squares method. Stress-strain data are employed to train EPR and develop EPR-based material models. A methodology is introduced to
incorporate the developed EPR models in FE method. It is shown that it is possible to construct the material stiffness (Jacobian) matrix using partial derivatives of the developed EPR models. The EPRbased Jacobian matrix is implemented in a FE model and a boundary value problem is used to verify the methodology. The results of the EPR-FEM are compared with those of standard FEM where conventional constitutive models are used to model the behaviour of materials. These results show that EPR-FEM can be successfully employed to analyse different engineering problems.

Item Type: Conference Proceedings
Title of Proceedings: ACME2012: Proceedings of the 20th UK National Conference of the Association for Computational Mechanics in Engineering
Additional Information: [1] Presented ACME2012 and included in the Proceedings of the 20th UK National Conference of the Association for Computational Mechanics in Engineering, held 26–28 March 2012, at the School of Mechanical, Aerospace and Civil Engineering, The University of Manchester, UK.
Uncontrolled Keywords: constitutive modelling, finite element, data mining, evolutionary techniques
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Pre-2014 Departments: School of Engineering
Related URLs:
Last Modified: 14 Oct 2016 09:24
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/9679

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